# RSSM Submission Package
## Social Networks, Gender, and Graduate Hiring in a Rentier State

**Dataset:** Harvard Dataverse doi:10.7910/DVN/R2W8AW  
**Journal:** Research in Social Stratification and Mobility  
**Author:** Khalifa Al Hatmi, UTAS Al Musanna College

---

## Package Contents

### Word Documents (for journal submission)
| File | Purpose |
|------|---------|
| `Title_Page_Social_Networks.docx` | Title page with author details, suggested reviewers, CRediT statement |
| `Cover_Letter_Social_Networks.docx` | Cover letter addressed to RSSM Editor-in-Chief |
| `Appendices_Social_Networks.docx` | Full appendices A–H (sample, design, diagnostics, interview guide, codebook, dataset variables) |
| `Social_Networks_Gender_RSSM.docx` | Main manuscript (double-blind) |

### R Analysis Scripts
| File | Contents |
|------|---------|
| `01_data_preparation.R` | Load Harvard Dataverse data; dummy coding of all 9 vignette attributes; employer variable coding; ICC calculation; merge |
| `02_multilevel_analysis.R` | Models M0–M2; Tables 2–3; Figures 1–3; marginal means |
| `03_robustness_checks.R` | Hausman test; pooled OLS; binary logit; log-transform; vignette fatigue; recruiter gender moderation |
| `05_qualitative_codebook.R` | Framework matrix structure; coding frequencies; intercoder kappa; illustrative quotes table |

### Stata Script
| File | Contents |
|------|---------|
| `04_stata_replication.do` | Full Stata replication using -mixed-, -melogit-, -margins-, -marginsplot-, -esttab-; SAS design code documented |

---

## Data Structure (Harvard Dataverse)

```
vignette_data.csv    — N = 2,280 rows (190 employers × 12 vignettes)
employer_data.csv    — N = 190 rows (one per employer)
interview_codebook.xlsx — qualitative coding (NVivo 12 export)
```

### Key Variables
- **Outcome 1:** `hire` — hiring propensity 0–10
- **Outcome 2:** `train` — expected trainability 0–10
- **Key IV (referral):** `referral` — none | inst_nocoop | inst_coop | employee | personal
- **Key IV (gender):** `gender` — female | male
- **Employer clustering:** `resp_id` (random intercept in all models)

---

## Software Requirements

**R (≥ 4.3.x):**
```r
pacman::p_load(tidyverse, haven, lme4, lmerTest, broom.mixed,
               performance, modelsummary, emmeans, marginaleffects,
               ggeffects, ggplot2, fixest, irr, flextable, officer)
```

**Stata (≥ 17):**
- Packages: `estout` (ssc install estout)

**SAS (v9.4):** For design replication only (PROC OPTEX documented in script 04)

---

## Reproducibility

Run scripts in order:
```
01_data_preparation.R   → creates data/df_prepared.rds
02_multilevel_analysis.R → creates output/Table2, Table3, Figures 1-3
03_robustness_checks.R  → creates output/TableA2_Robustness.docx
04_stata_replication.do → creates output/stata_main_results.rtf
05_qualitative_codebook.R → creates output/AppendixD_Quotes.docx
```

Expected runtime: ~5–10 minutes total on a modern laptop.

---

## Citation

Al Hatmi, K. (2026). *Social Networks, Gender, and Graduate Hiring in a Rentier State: Disentangling Referral Types and Ascriptive Signals in Omani Labour Markets.* [Manuscript submitted for publication]. Research in Social Stratification and Mobility.

Dataset: Al Hatmi, K. (2022). Replication data. Harvard Dataverse. https://doi.org/10.7910/DVN/R2W8AW
